Person:

Hunink, Maria

Objectives: To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS). Methods: We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as ≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance. Results: Re-analysing the variables used by Diamond Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model. Conclusions: Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up.

Aims: Much controversy exists concerning the efficacy of primary prophylactic implantable cardioverter-defibrillators (ICDs) in patients with low ejection fraction due to coronary artery disease (CAD) or dilated cardiomyopathy (DCM). This is also related to the bias created by function improving interventions added to ICD therapy, e.g. resynchronization therapy. The aim was to investigate the efficacy of ICD-only therapy in primary prevention in patients with CAD or DCM. Methods and results: Public domain databases, MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials, were searched from 1980 to 2009 for randomized clinical trials of ICD vs. conventional therapy. Two investigators independently abstracted the data. Pooled estimates were calculated using both fixed-effects and random-effects models. Eight trials were included in the final analysis (5343 patients). Implantable cardioverter-defibrillators significantly reduced the arrhythmic mortality [relative risk (RR): 0.40; 95% confidence interval (CI): 0.27–0.67] and all-cause mortality (RR: 0.73; 95% CI: 0.64–0.82). Regardless of aetiology of heart disease, ICD benefit was similar for CAD (RR: 0.67; 95% CI: 0.51–0.88) vs. DCM (RR: 0.74; 95% CI: 0.59–0.93). Conclusions: The results of this meta-analysis provide strong evidence for the beneficial effect of ICD-only therapy on the survival of patients with ischaemic or non-ischaemic heart disease, with a left ventricular ejection fraction ≤35%, if they are 40 days from myocardial infarction and ≥3 months from a coronary revascularization procedure.

Objectives: To determine and compare the diagnostic performance of stress myocardial perfusion imaging (MPI) for the diagnosis of obstructive coronary artery disease (CAD), using conventional coronary angiography (CCA) as the reference standard. Methods: We searched Medline and Embase for literature that evaluated stress MPI for the diagnosis of obstructive CAD using magnetic resonance imaging (MRI), contrast-enhanced echocardiography (ECHO), single-photon emission computed tomography (SPECT) and positron emission tomography (PET). Results: All pooled analyses were based on random effects models. Articles on MRI yielded a total of 2,970 patients from 28 studies, articles on ECHO yielded a sample size of 795 from 10 studies, articles on SPECT yielded 1,323 from 13 studies. For CAD defined as either at least 50 %, at least 70 % or at least 75 % lumen diameter reduction on CCA, the natural logarithms of the diagnostic odds ratio (lnDOR) for MRI (3.63; 95 % CI 3.26–4.00) was significantly higher compared to that of SPECT (2.76; 95 % CI 2.28–3.25; P = 0.006) and that of ECHO (2.83; 95 % CI 2.29–3.37; P = 0.02). There was no significant difference between the lnDOR of SPECT and ECHO (P = 0.52). Conclusion: Our results suggest that MRI is superior for the diagnosis of obstructive CAD compared with ECHO and SPECT. ECHO and SPECT demonstrated similar diagnostic performance.

Objectives: To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations. Design Retrospective pooled analysis of individual patient data. Setting 18 hospitals in Europe and the United States. Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. Results: We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory. Conclusions: Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates.

Purpose: To control for confounding bias from non-random treatment assignment in observational data, both traditional multivariable models and more recently propensity score approaches have been applied. Our aim was to compare a propensity score-stratified model with a traditional multivariable-adjusted model, specifically in estimating survival of hemodialysis (HD) versus peritoneal dialysis (PD) patients. Methods: Using the Dutch End-Stage Renal Disease Registry, we constructed a propensity score, predicting PD assignment from age, gender, primary renal disease, center of dialysis, and year of first renal replacement therapy. We developed two Cox proportional hazards regression models to estimate survival on PD relative to HD, a propensity score-stratified model stratifying on the propensity score and a multivariable-adjusted model, and tested several interaction terms in both models. Results: The propensity score performed well: it showed a reasonable fit, had a good c-statistic, calibrated well and balanced the covariates. The main-effects multivariable-adjusted model and the propensity score-stratified univariable Cox model resulted in similar relative mortality risk estimates of PD compared with HD (0.99 and 0.97, respectively) with fewer significant covariates in the propensity model. After introducing the missing interaction variables for effect modification in both models, the mortality risk estimates for both main effects and interactions remained comparable, but the propensity score model had nearly as many covariates because of the additional interaction variables. Conclusion: Although the propensity score performed well, it did not alter the treatment effect in the outcome model and lost its advantage of parsimony in the presence of effect modification.

Background: Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks. Methods and Findings: A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk. Conclusions: We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their individual outcomes with statin therapy. Please see later in the article for the Editors' Summary

BACKGROUND: Evidence shows that healthy diet, exercise, smoking interventions, and stress reduction reduce cardiovascular disease risk. We aimed to compare the effectiveness of these lifestyle interventions for individual risk profiles and determine their rank order in reducing 10-year cardiovascular disease risk. METHODS AND RESULTS: We computed risks using the American College of Cardiology/American Heart Association Pooled Cohort Equations for a variety of individual profiles. Using published literature on risk factor reductions through diverse lifestyle interventions-group therapy for stopping smoking, Mediterranean diet, aerobic exercise (walking), and yoga-we calculated the risk reduction through each of these interventions to determine the strategy associated with the maximum benefit for each profile. Sensitivity analyses were conducted to test the robustness of the results. In the base-case analysis, yoga was associated with the largest 10-year cardiovascular disease risk reductions (maximum absolute reduction 16.7% for the highest-risk individuals). Walking generally ranked second (max 11.4%), followed by Mediterranean diet (max 9.2%), and group therapy for smoking (max 1.6%). If the individual was a current smoker and successfully quit smoking (ie, achieved complete smoking cessation), then stopping smoking yielded the largest reduction. Probabilistic and 1-way sensitivity analysis confirmed the demonstrated trend. CONCLUSIONS: This study reports the comparative effectiveness of several forms of lifestyle modifications and found smoking cessation and yoga to be the most effective forms of cardiovascular disease prevention. Future research should focus on patient adherence to personalized therapies, cost-effectiveness of these strategies, and the potential for enhanced benefit when interventions are performed simultaneously rather than as single measures.

Objective: Peripheral arterial disease (PAD) often hinders the cardiac rehabilitation program. The aim of this study was evaluating the relative cost-effectiveness of new rehabilitation strategies which include the diagnosis and treatment of PAD in patients with coronary artery disease (CAD) undergoing cardiac rehabilitation. Data Sources: Best-available evidence was retrieved from literature and combined with primary data from 231 patients. Methods: We developed a Markov decision model to compare the following treatment strategies: 1. cardiac rehabilitation only; 2. ankle-brachial index (ABI) if cardiac rehabilitation fails followed by diagnostic work-up and revascularization for PAD if needed; 3. ABI prior to cardiac rehabilitation followed by diagnostic work-up and revascularization for PAD if needed. Quality-adjusted-life years (QALYs), life-time costs (US $), incremental cost-effectiveness ratios (ICER), and gain in net health benefits (NHB) in QALY equivalents were calculated. A threshold willingness-to-pay of $75 000 was used. Results: ABI if cardiac rehabilitation fails was the most favorable strategy with an ICER of $44 251 per QALY gained and an incremental NHB compared to cardiac rehabilitation only of 0.03 QALYs (95% CI: −0.17, 0.29) at a threshold willingness-to-pay of $75 000/QALY. After sensitivity analysis, a combined cardiac and vascular rehabilitation program increased the success rate and would dominate the other two strategies with total lifetime costs of $30 246 a quality-adjusted life expectancy of 3.84 years, and an incremental NHB of 0.06 QALYs (95%CI:−0.24, 0.46) compared to current practice. The results were robust for other different input parameters. Conclusion: ABI measurement if cardiac rehabilitation fails followed by a diagnostic work-up and revascularization for PAD if needed are potentially cost-effective compared to cardiac rehabilitation only.